Measurement of Charged Pion, Kaon, and Proton

EUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH (CERN)

CERN-EP-2017-091 2017/12/16

CMS-FSQ-16-004

Measurement of charged pion, kaon, and√ proton production in proton-proton collisions at s = 13 TeV

The CMS Collaboration∗

Abstract

Transverse momentum spectra√ of charged pions, kaons, and protons are measured in proton-proton collisions at s = 13 TeV with the CMS detector at the LHC. The particles, identiﬁed via their energy loss in the silicon tracker, are measured in the transverse momentum range of pT ≈ 0.1–1.7 GeV/c and rapidities |y| < √1. The pT spectra and integrated yields are compared to previous results at smaller s and to predictions of Monte Carlo event generators. The average pT increases with particle mass and charged√ particle multiplicity of the event. Comparisons with previous CMS results at s = 0.9, 2.76, and 7 TeV show that the average pT and the ratios of hadron yields feature very similar dependences on the particle multiplicity in the event, independently of the center-of-mass energy of the pp collision.

Published in Physical Review D as doi:10.1103/PhysRevD.96.112003. arXiv:1706.10194v2 [hep-ex] 7 Dec 2017

c 2017 CERN for the beneﬁt of the CMS Collaboration. CC-BY-4.0 license

∗See Appendix A for the list of collaboration members

1 Introduction The study of hadron production has a long history in high-energy particle, nuclear, and cosmic ray physics. The absolute yields and the transverse momentum (pT) spectra of identified hadrons in high-energy hadron-hadron collisions are among the most basic physical observ- ables. They can be used to improve the modeling of various key ingredients of Monte Carlo (MC) hadronic event generators, such as multiparton interactions, parton hadronization, and final-state effects (such as parton correlations in color, pT, spin, baryon and strangeness number, and collective flow) [1]. The dependence of the hadron spectra and yields on the impact parameter of the proton-proton (pp) collision provides additional valuable information to tune the corresponding MC parameters. Indeed, parton hadronization and final-state effects are mostly constrained from elementary e+e− collisions, whose final states are largely dominated by simple qq final states, whereas low-pT hadrons at the LHC issue from the fragmentation of multiple gluon “minijets” [1]. Such large differences have a particularly important impact on baryons and strange hadrons, whose production in pp collisions is not well reproduced by the existing models [2, 3], and also affect the modeling of hadronic interactions of ultrahigh-energy cosmic rays with Earth’s atmosphere [4]. Spectra of identified particles in pp collisions also constitute an important reference for high-energy heavy ion studies, where various final-state effects are known to modify the spectral shape and yields of different hadron species [5–9].

The√ present analysis uses pp collisions collected by the CMS experiment at the CERN LHC at s = 13 TeV and focuses on the measurement of the pT spectra of charged hadrons, identiﬁed primarily via their energy depositions in the silicon detectors. The analysis adopts the same methods as used in previous√ CMS measurements of pion, kaon, and proton production in pp and pPb collisions at s of 0.9, 2.76, and 7 TeV [2, 10], as well as those performed by the ALICE Collaboration at 2.76 and 7 TeV [3, 11].

2 The CMS detector and event generators A detailed description of the CMS detector can be found in Ref. [12]. The CMS experiment uses a right-handed coordinate system, with the origin at the nominal interaction point (IP) and the z axis along the counterclockwise-beam direction. The pseudorapidity η and rapidity y of a particle (in the laboratory frame) with energy E, momentum p, and momentum along the z axis pz are defined as η = − ln[tan(θ/2)], where θ is the polar angle with respect to the z axis and 1 y = 2 ln[(E + pz)/(E − pz)]. The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter. Within the 3.8 T field volume are the silicon pixel and strip tracker, the crystal electromagnetic calorimeter, and a brass and scintillator hadron calorimeter. The tracker measures charged particles within the range |η| < 2.4. It has 1440 silicon pixel and 15 148 silicon strip detector modules with thicknesses of either 300 or 500 µm, assembled in 13 detection layers in the central region. Beam pick-up timing for the experiment (BPTX) devices were used to trigger the detector readout. They are located around the beam pipe at a distance of 175 m from the IP on either side, and are designed to provide precise information on the bunch structure and timing of the incoming beams of the LHC. In this paper, distributions of identified hadrons produced in inelastic pp collisions are compared to predictions from MC event generators based on two different theoretical frameworks: perturbative QCD (PYTHIA6.426 [13] and PYTHIA8.208 [14]) and Reggeon field theory (EPOS v3400 [15]). On the one hand, the basic ingredients of PYTHIA6 and PYTHIA8 are (multiple) leading-order perturbative QCD 2 → 2 matrix elements, complemented with initial- and final-state parton radiation (ISR and FSR), folded with parton distribution functions in the proton, and the Lund 2 3 Event selection and reconstruction string model for parton hadronization. Two different “tunes” of the parameters governing the nonperturbative and semihard dynamics (ISR and FSR showering, multiple parton interactions, beam-remnants, final-state color-reconnection, and hadronization) are used: the PYTHIA6 Z2* [13, 16] and PYTHIA8 CUETP8M1 [16] tunings, based on fits to recent minimum bias and underlying event measurements at the LHC. On the other hand, EPOS starts off from the basic quantum field-theory principles of unitarity and analyticity of scattering amplitudes as imple- mented in Gribov’s Reggeon field theory [17], extended to include (multiple) parton scatter- ings via “cut (hard) Pomerons.” The latter objects correspond to color flux tubes that are finally hadronized also via the Lund string model. The version of EPOS used here is run with the LHC tune [18] which includes collective final-state string interactions resulting in an extra radial flow of the final hadrons produced in more central pp collisions.

3 Event selection and reconstruction The data used for the measurements presented in this paper were taken during a special low luminosity run where the average number of pp interactions in each bunch crossing was 1.0. A total of 7.0 × 106 collisions were recorded, corresponding to an integrated luminosity of approximately 0.1 nb−1. The event selection consisted of the following requirements: • at trigger level, the coincidence of signals from both BPTX devices, indicating the presence of both proton bunches crossing the interaction point; • offline, to have at least one reconstructed interaction vertex; • beam-halo and beam-induced background events, which usually produce an anoma- lously large number of pixel hits, were identified [19] and rejected. The event selection efficiency as well as the tracking and vertexing acceptance and efficiency are evaluated using simulated event samples produced with the PYTHIA8 (tune CUETP8M1) MC event generator, followed by the CMS detector response simulation based on GEANT4 [20]. Simulated events are reconstructed and analyzed in the same way as collision data events. The final results are given for an event selection corresponding to inelastic pp collisions, which will be presented in Sec. 6. According to the three MC event generators considered, the fraction of inelastic pp collisions not resulting in a reconstructed pp interaction amounts to about 14% ± 3%, where the uncertainty is based on the variance of the predictions coming from the event generators. These events are mostly diffractive ones with negligible central activity. The reconstruction of charged particles in CMS is limited by the acceptance of the tracker (|η| < 2.4) and by the decreasing tracking efficiency at low momentum caused by multiple scattering and energy loss. The identification of particle species using specific ionization (Sec. 4) is restricted to p < 0.15 GeV/c for electrons, p < 1.20 GeV/c for pions, p < 1.05 GeV/c for kaons, and p < 1.70 GeV/c for protons [2, 10]. Pions are measured up to a higher momentum than kaons because of their larger relative abundance. In order to have a common kinematic region where pions, kaons, and protons can all be identified, the range |y| < 1 is chosen for this measurement.

The extrapolation of particle spectra into unmeasured (y, pT) regions is model dependent, particularly at low pT. A precise measurement therefore requires reliable track reconstruction down to the lowest possible pT values. Special tracking algorithms [21], already used in previous studies [2, 10, 19, 22], made it possible to extend the present analysis to pT ≈ 0.1 GeV/c with high reconstruction efﬁciency and low background. Compared to the standard tracking 3

CMS simulation 0.05 1.2 pp √s = 13 TeV

1 0.04

0.8 Accep. Effic. 0.03 π+ 0.6 K+ p 0.02 0.4 Acceptance or efficiency

0.01 Misreconstructed-track rate 0.2 Misrec. rate

0 0 0 0.5 1 1.5 2

pT [GeV/c] Figure 1: Acceptance (open markers, left scale), tracking efficiency (filled markers, left scale), and misreconstructed-track rate (right scale) in the range |η| < 2.4 as a function of pT for positively charged pions, kaons, and protons. The values are very similar for negatively charged particles. algorithm used in CMS, these algorithms feature special track seeding and cleaning, hit cluster shape filtering, modified trajectory propagation, and track quality requirements. The charged- pion mass is assumed when fitting particle momenta.

The acceptance of the tracker (Ca) is defined as the fraction of primary charged particles leaving at least two hits in the pixel detector. Based on MC studies, it is flat in the region |η| < 2 and pT > 0.4 GeV/c, and at values of 96%–98% as can be seen in Fig. 1. The loss of acceptance at pT < 0.4 GeV/c is caused by energy loss and multiple scattering, which are both functions of particle mass. The reconstruction efficiency (Ce), which is defined as the fraction of accepted charged particles that result in a successfully reconstructed trajectory, is usually in the range 80%–90%. It decreases at low pT, also in a mass-dependent way. The misreconstructed-track rate (Cf), defined as the fraction of reconstructed primary charged tracks without a corresponding genuine primary charged particle, is very small, reaching 1% for pT < 0.2 GeV/c. The probability of reconstructing multiple tracks (Cm) from a single charged particle is about 0.1%, mostly from particles spiralling in the strong magnetic field of the CMS solenoid. The efficiencies and background rates (misreconstruction, multiple reconstruction) are found not to depend on the charged-particle multiplicity of the event in the range of multiplicities of interest for this analysis. They largely factorize in η and pT, but for the final corrections (Sec. 5) an (η, pT) matrix is used. The region where pp collisions occur (beam spot) is measured from the distribution of reconstructed interaction vertices. Since the bunches are very narrow in the plane transverse to the beam direction (with a width of about 50 µm for this special run), the x–y location of the interaction vertices is well constrained; conversely, their z coordinates are spread over a relatively long distance and must be determined on an event-by-event basis. The vertex position is determined using reconstructed tracks that have pT > 0.1 GeV/c and originate from the vicinity of the beam spot, i.e. their transverse impact parameters dT (with respect to the center of the beam spot) satisfy the condition dT < 3 σT. Here σT is the quadratic sum of the uncertainty in the value of dT and the root mean square of the beam spot distribution in the transverse plane. In order to reach higher efficiency in special-topology low-multiplicity events, an ag- glomerative vertex reconstruction algorithm [23] is used, with the z coordinates of the tracks (and their uncertainties) at the point of closest approach to the beam axis as input. The distance 4 4 Estimation of energy loss rate and yield extraction distributions of reconstructed vertex pairs in data indicates that the fraction of merged vertices (with tracks from two or more true vertices) and split vertices (two or more reconstructed vertices with tracks from a single true vertex) is about 1%. For single-vertex events, there is no minimum requirement on the number of tracks associated with the vertex (those assigned to it during vertex finding), and even one-track vertices, which are defined as the point of closest approach of the track to the beam line, are allowed. The fraction of events with more than one (three) reconstructed primary vertices is about 26% (1.8%). Only events with three or fewer reconstructed primary vertices were considered and only tracks associated with a primary vertex are used in the analysis. The vertex resolution in the z direction is a strong function of the number of reconstructed tracks and is always less than 0.1 cm. The distribution of the z coordinates of the reconstructed primary vertices is Gaussian with a width of σ = 4.2 cm. Simulated events are reweighted in order to have the same vertex z coordinate distribution as in collision data. The contribution to the hadron spectra from particles of nonprimary origin arising from the decay of particles with proper lifetime τ > 10−12 s was subtracted. The main sources of these 0 + − secondary particles are weakly decaying particles, mostly KS, Λ/Λ, and Σ /Σ . According to the simulations, this correction (Cs) is approximately 1% for pions and rises to 15% for protons with pT ≈ 0.2 GeV/c. Because none of these particles decay weakly into kaons, the correction for kaons is less than 0.1%. Charged particles from interactions of primary particles or their decay products with detector material are suppressed by the impact parameter cuts described above. For p < 0.15 GeV/c, electrons can be clearly identified based on their energy loss (Fig. 2, left) and their contamination of the hadron yields is below 0.2%. Although muons cannot be distinguished from pions, according to MC predictions their fraction is below 0.05%. Since both contaminations are negligible with respect to the final uncertainties, no corrections are applied.

4 Estimation of energy loss rate and yield extraction For this paper an analytical parametrization [24] is used to model the energy loss of charged particles in the silicon detectors. It provides the probability density P(∆|ε, l) of finding an energy deposit ∆, if the most probable energy loss rate ε at a reference path length l0 = 450 µm and the path length l are known. The choice of 450 µm is motivated by being the approximate average path length traversed in the silicon detectors. The value of ε depends on the momentum and mass m of the charged particle. The parametrization is used in conjunction with a maximum likelihood fit for the estimate of ε. All details of the methods described below are given in Ref. [2]. Using the cluster shape filtering mentioned in Sec. 3, only hit clusters compatible with the particle trajectory are used. For clusters in the pixel detector, the energy deposits are calculated based on the individual pixel deposits. In the case of clusters in the strip detector, the energy deposits are corrected for truncation performed by the readout electronics and for losses due to deposits below threshold because of capacitive coupling and cross-talk between neighboring strips. The readout threshold, the strength of coupling, and the standard deviation of the Gaus- sian noise for strips are determined from data. The response of all readout chips is calibrated with multiplicative gain correction factors. After the readout chip calibration, the measured energy deposit spectra for each silicon sub- detector are compared to the expectations of the energy loss model as a function of p/m and 5

CMS CMS 6 pp √s = 13 TeV pp √s = 13 TeV η = 0.35 Data 1.8 + 1.6 e p = 0.82 GeV/c p = 0.775 GeV/c Fit 20 1.4 π+ T π 1.2 + 5 2 1.0 K χ /ndf = 1.02 K 8.0 p δπ = -0.013 p 6.0 δ = 0.027 10 4 K 4.0 ] δp = 0.005 2 2.0 3 10 0.0 1 10 5 3 0 α = 0.995 10

[MeV/cm] π ε αK = 0.964 10-1 Counts [10 2 αp = 0.973 10-2 2 10-3 1 10-4 1 2 5 10 20 1 0.1 0.2 0.5 1 2 5 10 20 0 1 2 5 10 20 p [GeV/c] ε [MeV/cm] Figure 2: Left: distribution of ε as a function of total momentum p, for positively charged reconstructed particles (ε is the most probable energy loss rate at a reference path length l0 = 450 µm). The color scale is shown in arbitrary units and is linear. The curves show the expected ε for electrons, pions, kaons, and protons (Eq. (30.11) in Ref. [25]). Right: example ε distribution at η = 0.35 and pT = 0.775 GeV/c (bin centers), with bin widths ∆η = 0.1 and ∆pT = 0.05 GeV/c. Scale factors (α) and shifts (δ) are indicated. The inset shows the distribution with logarithmic vertical scale. l using particles satisfying tight identification criteria. These comparisons allow the computa- tion of hit-level corrections to the energy loss model that is used to estimate the particle energy loss rate ε and its associated distribution. The best value of ε for each track is calculated from the measured energy deposits by minimiz- ing the negative log-likelihood function of the combined energy deposit for all hits (index i) 2 associated with the particle trajectory, χ = −2 ∑i ln P(∆i|ε, li), where the probability density functions include the hit-level corrections mentioned above. Hits with incompatible energy deposits (contributing more than 12 units to the combined χ2) are excluded. For the determination of ε, removal of at most one hit per track is allowed; this affected about 1.5% of the tracks. Low-momentum particles can be identified unambiguously and can therefore be counted (Fig. 2). Conversely, at high momenta (above about 0.5 GeV/c for pions and kaons and above 1.2 GeV/c for protons) the ε bands overlap. Therefore the particle yields need to be determined by means of a series of template fits in ε, in bins of η and pT (Fig. 2, right panel). Fit templates with the expected ε distributions for all particle species (electrons, pions, kaons, and protons) are obtained from reconstructed tracks in data. All track parameters and hit-related quantities are kept but, in order to populate the distributions, the energy deposits are regenerated by sampling from the hit-level corrected analytical parametrization assuming a given particle type. Possi- ble residual discrepancies between the observed and expected ε distributions, present in some regions of the parameter space (mostly at low pT), are taken into account by means of the track- level corrections consisting, as for the hit-level corrections, of a linear transformation of the parametrization using scale factors and shifts. For a less biased determination of these track- level residual corrections, enriched samples of each particle type are employed for determining starting values of the parameters to be fitted. For electrons and positrons, photon conversions in the beam-pipe and in the innermost pixel layer are used. For high-purity pion and enriched 0 proton samples, weakly decaying hadrons are selected (KS, Λ/Λ). The following criteria and methods described in Ref. [2] are also exploited to better constrain the parameters of the fits: 6 5 Yield extraction and systematic uncertainties

2 fitting the ε distributions in slices of number of hits (nhits) and track fit χ /ndf (where ndf is number of degrees of freedom) simultaneously; setting constraints on the nhits distribution for specific particle species; imposing the expected continuity of track-level residual corrections in adjacent (η, pT) bins; and using the expected convergence of track-level residual corrections as the ε values of two particle species approach each other at large momentum. Distributions of ε as a function of total momentum p for positive particles are plotted in the left panel of Fig. 2 and compared to the predictions of the energy loss parametrization [24] for electrons, pions, kaons, and protons. The results of the (iterative) ε fits are the yields for each particle species and charge in bins of (η, pT) or (y, pT), both inclusive and divided into classes of reconstructed primary charged-track multiplicity. Although pion and kaon yields could not be determined for p > 1.30 GeV/c, their sum is measured. This information is an important constraint when fitting the pT spectra.

5 Yield extraction and systematic uncertainties

The measured yields in each (η, pT) bin, ∆Nmeasured, are ﬁrst corrected for the misreconstructed- track rate Cf and the fraction of secondary particles Cs:

0 ∆N = ∆Nmeasured (1 − Cf)(1 − Cs). (1)

The bin widths are ∆η = 0.1 and ∆pT = 0.05 GeV/c. The distributions are then unfolded to take into account bin migrations due to the finite η and pT resolutions. The η distribution of the tracks is almost flat and the η resolution is significantly smaller than the bin width. At the same time the pT distribution is steep in the low-momentum region and separate pT-dependent corrections in each η slice are necessary. For that, an unfolding procedure with a linear regularization method (Tikhonov regularization [26]) is used, based on response matrices obtained from PYTHIA8 MC samples separately for each particle species. This procedure guarantees that the uncertainties associated with the assumption of the pion mass in the track fitting step are taken into account. The bin purities of the matrices are above 80%–90%. The chosen regularization term reflects that the original distribution changes only slowly, but that that particular choice has negligible influence on the results. Further corrections for acceptance, efficiency, and multiple track reconstruction probability are applied:

1 d2N 1 ∆N0 = , (2) Nev dη dpT corrected Ca Ce (1 + Cm) Nev∆η∆pT where Nev is the corrected number of inelastic pp collisions in the data sample. Bins that meet at least one of the following criteria are not used in order to ensure robustness of the ﬁts described below and to minimize the impact on the systematic uncertainties: acceptance less than 50%; efﬁciency less than 50%; multiple-track rate greater than 10%; multiplicity below 80 tracks. 2 2 Finally, the η-differential yields d N/dη dpT are transformed into d N/dy dpT yields by mul- tiplying with the Jacobian of the η to y transformation (E/p), and the (η, pT) bins are mapped onto a (y, pT) grid. The differential yields exhibit a slight (5%–10%) dependence on y in the narrow region considered (|y| < 1), an effect that decreases with the event multiplicity. The yields as a function of pT are obtained averaged over the rapidity window. 7

The pT distributions are fit using a Tsallis-Pareto-type function, which empirically describes both the low-pT exponential and the high-pT power-law behaviors while employing only a few parameters. Based on the good reproduction of previous measurements of unidentified and identified particle spectra [2, 10, 19, 27], the following form of the distribution [28, 29] is used:

2 −n d N dN mT − m c = C pT 1 + , (3) dy dpT dy nT where

(n − 1)(n − 2) C = (4) nT[nT + (n − 2)m c]

q 2 2 and mT = (mc) + pT. The free parameters are the integrated yield dN/dy, the exponent n, and the parameter T. According to some models of particle production based on nonex- tensive thermodynamics [29], the parameter T is connected with the average particle energy, while n characterizes the “nonextensivity” of the process, i.e. the departure of the spectra from a Boltzmann distribution (n = ∞). Equation (3) is useful for extrapolating the spectra down to zero and up to high pT, and thereby extracting hpTi and hdN/dyi. Its validity for different multiplicity bins is cross-checked by fitting MC spectra in the pT ranges where there are data points, and verifying that the fitted values of hpTi and hdN/dyi are consistent with the generated values. Nevertheless, for a more robust estimation of both hpTi and hdN/dyi, the unfolded bin-by-bin yield values and their uncertainties are used in the measured range while the fitted functions are employed for the extrapolation into the unmeasured regions. As discussed earlier, pions and kaons cannot be unambiguously distinguished at high mo- 2 menta. For this reason the pion-only, the kaon-only, and the joint pion and kaon d N/dy dpT distributions are fitted for |y| < 1 and p < 1.20 GeV/c, |y| < 1 and p < 1.05 GeV/c, and |η| < 1 and 1.05 < p < 1.7 GeV/c, respectively. Since the ratio p/E for the pions (which are more abun- dant than kaons) at these momenta can be approximated by pT/mT at η ≈ 0, Eq. (3) becomes:

− d2N dN p2 m − m c n ≈ C T 1 + T . (5) dη dpT dy mT nT

Moreover, below pT values of 0.1–0.3 GeV the detector acceptance and the tracking efﬁciency signiﬁcantly decrease. The Tsallis-Pareto function is used to extrapolate the measured yields both into this latter region and to the region at high momenta such that the integrated yield (dN/dy) and the average transverse momentum (hpTi) can be reported for the full pT range. This choice allows measurements performed by different experiments in various collision systems and center-of-mass energies to be compared.

The fractions of particles outside the measured pT range are 15%–30% for pions, 40%–50% for kaons, and 20%–35% for protons, depending on the track multiplicity of the event. The systematic uncertainties are very similar to those in Ref. [2] and are summarized in Table 1. They are obtained from the comparison of different MC event generators, differences between data and simulation, or based on previous studies (hit inefficiency, misalignment). The uncertainties in the corrections Ca, Ce, Cf and Cm, which are related to the event selection, and the effects of pileup, are fully or mostly correlated and are treated as normalization uncertainties: 8 6 Results altogether they propagate to a 3.0% uncertainty in the yields and a 1.0% uncertainty in the average pT. In order to study the influence of the high-pT extrapolation on the hdN/dyi and hpTi averages, the reciprocal of the exponent (1/n) of the fitted Tsallis-Pareto function was increased and decreased by ±0.05 only in the region above the highest measured pT; in this same region both the function and its first derivative were required to fit continuously the data points. The choice of the magnitude for the variation is motivated by the fitted 1/n values and their distance from a Boltzmann distribution. The resulting functions are plotted in Fig. 3 as dotted lines (though they are mostly indistinguishable from the nominal fit curves). The high-pT extrapolation introduces systematic uncertainties of 1–3% for hdN/dyi, and 4–8% for hpTi. The systematic uncertainty related to the low pT extrapolation is small compared to the contributions from other sources and therefore is not included in the combined systematic uncertainty of the measurement. The tracker acceptance and the track reconstruction efficiency generally have small uncertainties (1 and 3%, respectively), but at very low pT they reach 6%. For the multiple-track and misreconstructed-track rate corrections, the uncertainty is assumed to be 50% of the correction, while for the correction for secondary particles it is estimated to be 25% based on the differences between predictions of MC event generators and data. These bin-by-bin, largely uncorrelated uncertainties are caused by the imperfect modeling of the detector: regions with incorrectly modeled tracking efficiency, alignment uncertainties, and channel-by-channel varying hit efficiency. All these effects are taken as uncorrelated. The statistical uncertainties in the extracted yields are given by the fit uncertainties. Varia- tions of the track-level correction parameters, incompatible with statistical fluctuations, are observed. They are used to estimate the systematic uncertainties in the fitted scale factors and shifts and are at the level of 10−2 and 2 × 10−3, respectively. The systematic uncertainties in the yields in each bin are thus obtained by refitting the histograms with the parameters changed by these amounts. For the present measurement, systematic uncertainties dominate over the statistical ones. The systematic uncertainties originating from the unfolding procedure are also studied. Since the pT response matrices are close to diagonal, the unfolding of the pT distributions does not in- troduce substantial uncertainties. The correlations between neighboring pT bins are neglected, and therefore statistical uncertainties are regarded as uncorrelated. The systematic uncertainty of the fitted yields is in the range 1%–10%, depending primarily on total momentum.

6 Results The results discussed in the following are averaged over the rapidity range |y| < 1. In all cases, error bars in the ﬁgures indicate the uncorrelated statistical uncertainties, while boxes show the uncorrelated systematic uncertainties. The fully correlated normalization uncertainty is not shown. For the pT spectra, the average transverse momentum hpTi, and the ratios of particle yields, the data are compared to the predictions of PYTHIA8, EPOS, and PYTHIA6.

6.1 Inclusive measurements The transverse momentum distributions of positively and negatively charged hadrons (pions, kaons, protons) are shown in Fig. 3, along with the results of the ﬁts to the Tsallis-Pareto parametrization [Eqs. (3) and (5)]. The ﬁts are of good quality with χ2/ndf values in the range 0.4–1.2 (Table 2). Figure 4 presents the same data compared to the PYTHIA8, EPOS, and PYTHIA6 predictions. While pions are described well by all three generators, kaons are best modelled by 6.1 Inclusive measurements 9

Table 1: Summary of the systematic uncertainties affecting the pT spectra. Values in parentheses indicate uncertainties in the hpTi measurement. Representative, particle-specific uncertainties (π, K, p) are given for pT = 0.6 GeV/c in the third group of systematic uncertainties. Uncertainty Propagated Source of the source [%] yield uncertainty [%] Fully correlated, normalization Correction for event selection 3.0 (1.0) Pileup correction (merged and split vertices) 0.3 3–4 (5–9) High-pT extrapolation 1–3 (4–8) Mostly uncorrelated Pixel hit efficiency 0.3 0.3 Misalignment, different scenarios 0.1 Mostly uncorrelated, (y, pT)-dependent π K p Acceptance of the tracker 1–6 1 1 1 Efficiency of the reconstruction 3–6 3 3 3 Multiple-track reconstruction 50% of the corr. — — — Misreconstructed-track rate 50% of the corr. 0.1 0.1 0.1 Correction for secondary particles 25% of the corr. 0.2 — 2 Fit of the ε distributions 1–10 1 2 1

CMS CMS + − pp √s = 13 TeV π pp √s = 13 TeV π 6 + 6 − K x10 −K x10 p x25 p− x25− π++K+ π +K

] 5 ] 5 -1 -1

4 4 [(GeV/c) [(GeV/c) T T

3 3 N / dy dp N / dy dp 2 2 d d

ev 2 ev 2 1/N 1/N

1 1

0 0 0 0.5 1 1.5 2 0 0.5 1 1.5 2

pT [GeV/c] pT [GeV/c] Figure 3: Transverse momentum distributions of identified charged hadrons (pions, kaons, protons, sum of pions and kaons) from inelastic pp collisions, in the range |y| < 1, for positively (left) and negatively (right) charged particles. Kaon and proton distributions are scaled as shown in the legends. Fits to Eqs. (3) and (5) are superimposed. For the π+K fit, only the region corresponding to the range |η| < 1 and 1.05 < p < 1.7 GeV/c is plotted. Boxes show the uncorrelated systematic uncertainties, while error bars indicate the uncorrelated statistical uncertainties (barely visible). The fully correlated normalization uncertainty (not shown) is 3.0%. Dotted lines (mostly indistinguishable from the nominal fit curves) illustrate the effect of varying the inverse exponent (1/n) of the Tsallis-Pareto function by ±0.05 beyond the highest- pT measured point. 10 6 Results

CMS CMS 1 1 10 10 − √ π+ √ π pp s = 13 TeV + pp s = 13 TeV − K −K p p ] ] -1 Pythia8 CUETP8M1 -1 Pythia8 CUETP8M1 100 EPOS LHC 100 EPOS LHC Pythia6 Z2* Pythia6 Z2* [(GeV/c) [(GeV/c) T T N / dy dp N / dy dp 2 -1 2 -1 d 10 d 10 ev ev 1/N 1/N

10-2 10-2 0 0.5 1 1.5 2 0 0.5 1 1.5 2

pT [GeV/c] pT [GeV/c] Figure 4: Transverse momentum distributions of identiﬁed charged hadrons (pions, kaons, protons) from inelastic pp collisions, in the range |y| < 1, for positively (left) and negatively (right) charged particles. Measured values (same as in Fig. 3) are plotted together with predictions from PYTHIA8, EPOS, and PYTHIA6. Boxes show the uncorrelated systematic uncertainties, while error bars indicate the uncorrelated statistical uncertainties (hardly visible). The fully correlated normalization uncertainty (not shown) is 3.0%.

Table 2: Fit results for dN/dy, n, and T (obtained via Eqs. (3) and (5)), associated goodness- of-ﬁt values, and extracted hdN/dyi and hpTi averages, for charged pion, kaon, and proton spectra measured in the range |y| < 1 in inelastic pp collisions at 13 TeV. Combined statistical and systematic uncertainties are given.

2 Particle dN/dy n T [GeV/c] χ /ndf hdN/dyi hpTi [GeV/c] π+ 2.833 ± 0.031 5.2 ± 0.2 0.119 ± 0.003 6.8/19 2.843 ± 0.034 0.51 ± 0.03 π− 2.733 ± 0.029 5.9 ± 0.2 0.130 ± 0.003 22/19 2.746 ± 0.031 0.50 ± 0.03 K+ 0.318 ± 0.021 15 ± 18 0.231 ± 0.025 7.3/14 0.318 ± 0.007 0.67 ± 0.03 K− 0.332 ± 0.026 7.7 ± 4.6 0.217 ± 0.024 5.0/14 0.331 ± 0.011 0.75 ± 0.05 p 0.169 ± 0.007 4.7 ± 0.8 0.222 ± 0.016 8.9/23 0.169 ± 0.004 1.10 ± 0.12 p 0.162 ± 0.006 5.3 ± 1.1 0.237 ± 0.016 8.4/23 0.162 ± 0.004 1.07 ± 0.09

PYTHIA8 and EPOS. For protons and very low pT pions only PYTHIA8 gives a good description of the data. Ratios of particle yields as a function of the transverse momentum are plotted in Fig. 5. Only PYTHIA8 is able to predict both the K/π and p/π ratios as a function of pT. The ratios of the yields for oppositely charged particles are close to one (Fig. 5, right), as expected at this center-of-mass energy in the central rapidity region.

6.2 Multiplicity-dependent measurements

The study of the pT spectra as a function of the event track multiplicity is motivated partly by the intriguing hadron correlations measured in pp and pPb collisions at high track multiplicities [30–33], suggesting possible collective effects in “central” collisions at the LHC. We have also observed that in pp collisions at LHC energies [2, 10], the characteristics of particle 6.2 Multiplicity-dependent measurements 11

CMS CMS 0.35 pp √s = 13 TeV pp √s = 13 TeV 1.4 0.3

0.25 1.2

0.2 1 0.15 Yield ratios Yield ratios

0.1 0.8 Pythia8 CUETP8M1 EPOS LHC Pythia6 Z2* 0.05 − π /π+ + − π+ π− 0.6 − + (K +K− )/( +− ) −K /K (p+p)/(π++π ) p/p 0 0 0.5 1 1.5 2 0 0.5 1 1.5 2

pT [GeV/c] pT [GeV/c] Figure 5: Ratios of particle yields, K/π and p/π (left) and opposite-charge ratios (right), as a function of transverse momentum. Error bars indicate the uncorrelated statistical uncertainties, while boxes show the uncorrelated systematic uncertainties. In the left panel, curves indicate predictions from PYTHIA8, EPOS, and PYTHIA6.

Table 3: Relationship between the number of reconstructed tracks (Nrec) and the average number of corrected tracks (hNtracksi) in the region |η| < 2.4 in the 18 multiplicity classes considered.

Nrec 0–9 10–19 20–29 30–39 40–49 50–59 60–69 70–79 80–89 90–99 100–109 110–119 120–129 130–139 140–149 150–159 160–169 170–179 hNtracksi 7 16 28 40 51 63 74 85 97 108 119 130 141 151 162 172 183 187 production (hpTi, ratios of yields) are strongly correlated with the particle multiplicity in the event, which is in itself closely related to the number of underlying parton-parton interactions, independently of the concrete center-of-mass energy of the pp collision.

The event track multiplicity, Nrec, is defined as the number of tracks with |η| < 2.4 reconstructed using the same algorithm as for the identified charged hadrons [21]. The event multiplicity is divided into 18 classes as defined in Table 3. To facilitate comparisons with models, the event charged-particle multiplicity over |η| < 2.4 (Ntracks) is determined for each multiplicity class by correcting Nrec for the track reconstruction efficiency, which is estimated with the PYTHIA8 simulation in (η, pT) bins. The corrected yields are then integrated over pT, down to zero yield at pT = 0 (with a linear extrapolation below pT = 0.1 GeV/c). Finally, the integrals for each η slice are summed up. The average corrected charged-particle multiplicity hNtracksi is shown in Table 3 for each event multiplicity class. The value of hNtracksi is used to identify the multiplicity class in Figs. 6–9. Transverse-momentum distributions of pions, kaons, and protons, measured over |y| < 1 and normalized such that the fit integral is unity, are shown in Fig. 6 for various multiplicity classes. The distributions of negatively and positively charged particles are summed. The Tsallis-Pareto parametrization is fitted to the distributions with χ2/ndf values in the range 0.3–2.3 for pions, 0.2–2.6 for kaons, and 0.1–0.8 for protons. It is observed that for kaons and protons, the parameter T increases with multiplicity, while for pions T slightly increases and the exponent n 12 6 Results

CMS CMS √ ± √ ± 4.5 pp s = 13 TeV π 3.5 pp s = 13 TeV K

4 3 3.5 141 2.5 3 162 119 2.5 141 2 97 119 2 1.5 97 74 [normalized to fit integral] [normalized to fit integral] T 1.5 74 T 1 51

dN/dp 1 51 dN/dp 28 0.5 0.5 28 7 7 0 0 0 0.5 1 1.5 2 0 0.5 1 1.5 2

pT [GeV/c] pT [GeV/c] CMS − pp √s = 13 TeV p,p 3

141 2.5

119 2 97

1.5 74 [normalized to fit integral] T 1 51

dN/dp 28 0.5

7 0 0 0.5 1 1.5 2

pT [GeV/c] Figure 6: Transverse momentum distributions of charged pions (top left), kaons (top right), and protons (bottom), normalized such that the fit integral is unity, in every selected multiplicity class (hNtracksi values are indicated) in the range |y| < 1, fitted with the Tsallis-Pareto parametrization (solid lines). For better visibility, the result for any given hNtracksi bin is shifted by 0.4 units with respect to the adjacent bins. Error bars indicate the uncorrelated statistical uncertainties, while boxes show the uncorrelated systematic uncertainties. Dotted lines (mostly indistinguishable from the nominal fit curves) illustrate the effect of varying the inverse exponent (1/n) of the Tsallis-Pareto function by ±0.05 beyond the highest-pT measured point. 6.2 Multiplicity-dependent measurements 13

CMS CMS

0.16 pp √s = 13 TeV pp √s = 13 TeV 1.4 0.14

0.12 1.2

0.1

1 0.08 Yield ratios Yield ratios 0.06 0.8 0.04

− + 0.02 Pythia8 CUETP8M1 0.6 π /π EPOS LHC (K++K−)/(π++π−) K−/K+ Pythia6 Z2* (p+p)/(− π++π−) p/p− 0 0 50 100 150 200 0 50 100 150 200

〈Ntracks〉 〈Ntracks〉 Figure 7: Ratios of particle yields in the range |y| < 1 as a function of the corrected track multiplicity for |η| < 2.4. The K/π and p/π values are shown in the left panel, and opposite- charge ratios are plotted in the right panel. Error bars indicate the uncorrelated combined uncertainties, while boxes show the uncorrelated systematic uncertainties. In the left panel, curves indicate predictions from PYTHIA8, EPOS, and PYTHIA6.

CMS

1.6 pp √s = 13 TeV Pythia8 CUETP8M1 1.4 EPOS LHC Pythia6 Z2*

1.2

1 [GeV/c] 〉 T p

〈 0.8

0.6

0.4 π± K± p,p− 0.2 0 50 100 150 200

〈Ntracks〉 Figure 8: Average transverse momentum of identiﬁed charged hadrons (pions, kaons, protons) in the range |y| < 1, as functions of the corrected track multiplicity for |η| < 2.4, computed assuming a Tsallis-Pareto distribution in the unmeasured range. Error bars indicate the uncorrelated combined uncertainties, while boxes show the uncorrelated systematic uncertainties. The fully correlated normalization uncertainty (not shown) is 1.0%. Curves indicate predictions from PYTHIA8, EPOS, and PYTHIA6. 14 6 Results

CMS CMS 13 TeV 13 TeV pp ± 0.16 pp − − 1.6 π (K++K )/(π++π ) ± − π+ π− K − (p+p)/( + ) p,p 0.14 1.4

0.12 1.2 0.1 1

[GeV/c] 0.08 〉 T p Yield ratios 〈 0.8 0.06

0.6 0.04 0.9 TeV 2.76 TeV 7 TeV ± ± ± 0.4 π π π 0.02 0.9 TeV 2.76 TeV 7 TeV ± ± ± π π π K − K − K − K/ K/ K/ p,p p,p p,p p/π p/π p/π 0.2 0 0 50 100 150 200 0 50 100 150 200 〈 〉 〈 〉 Ntracks Ntracks Figure 9: Average transverse momentum of identified charged hadrons (pions, kaons, protons; left panel) and ratios of particle yields (right panel) in the range√ |y| < 1 as functions of the corrected track multiplicity for |η| < 2.4, for pp collisions at s = 13 TeV (filled symbols) and at lower energies (open symbols) [2]. Both hpTi and yield ratios are computed assuming a Tsallis-Pareto distribution in the unmeasured range. Error bars indicate the uncorrelated combined uncertainties, while boxes show the uncorrelated systematic uncertainties. For hpTi the fully correlated normalization uncertainty (not shown) is 1.0%. In both plots, lines are drawn to guide the eye (gray solid: 0.9 TeV, gray dotted: 2.76 TeV, black dash-dotted: 7 TeV, colored solid: 13 TeV). slightly decreases with multiplicity. The ratios of particle yields are displayed as functions of track multiplicity in Fig. 7. The K/π and p/π ratios are relatively flat as a function of hNtracksi, and none of the models is able to accurately reproduce the track multiplicity dependence. The ratios of yields of oppositely charged particles are independent of hNtracksi as shown in the right panel of Fig. 7. The average transverse momentum hpTi is shown as a function of multiplicity in Fig. 8. Although PYTHIA8 gives a good description of the (multiplicity integrated) inelastic pT spectra (Fig. 4), none of the MC event generators reproduces well the multiplicity dependence of hpTi for all particle species. In particular, all generators overestimate the measured values for kaons. Pions are well described by PYTHIA6 and EPOS, while protons are best described by PYTHIA8. In the lower multiplicity events, with fewer than 50 tracks, we observe a reasonable agreement between the data and the MC generator predictions for the different particle yields. However in higher multiplicity events, the measured kaon (proton) yield is smaller (higher) than predicted by the models. This indicates that the MC parameters that control the strangeness and baryon production as a function of parton multiplicity, need additional fine-tuning.

6.3 Comparisons with lower energy pp data The comparison of these results with lower-energy pp data taken at various center-of-mass energies (0.9, 2.76, and 7 TeV) [2] is presented in Fig. 9, where the track-multiplicity dependence of hpTi (left) and the particle yield ratios (K/π and p/π, right) are shown. In the previous publication [2], the ﬁnal results are corrected to a particle-level selection that requires at least 15

CMS CMS 10 pp DS pp DS’ pp inel pp DS pp inel ± ± π± π± π± 1.4 π π ± ± ± ± ± K K K K − K − p,p− p,p− p,p− p,p p,p 1.2

〉 1 [GeV/c] 〉 dN/dy 0.8 〈 T p 〈

0.6

0.4 0.1

0.2 0.5 1 2 5 10 0.5 1 2 5 10 √s [TeV] √s [TeV]

Figure 10: Average rapidity densities hdN/dyi (left) and average transverse momenta hpTi (right) for |y| < 1 as functions of center-of-mass energy for pp collisions (with data at 0.9, 2.76, and 7 TeV [2]), for charge-averaged pions, kaons, and protons. In the left plot the pp DS’ results at 13 TeV have been extrapolated from the inelastic values using simulation. Error bars indicate the uncorrelated combined uncertainties, while boxes show the uncorrelated systematic uncertainties. The curves show parabolic (hdN/dyi) or linear (for hpTi) ﬁts in ln s. one particle (with proper lifetime τ > 10−18 s) with E > 3 GeV in the range −5 < η < −3 and at least one in the range 3 < η < 5. This selection is referred to as the “double-sided” (DS) selection. Average rapidity densities hdN/dyi and average transverse momenta hpTi of charge-averaged pions, kaons, and protons as a function of center-of-mass energy are shown in Fig. 10 corrected to the DS selection (pp DS’). Based on the predictions of the three MC event generators studied, the inelastic hdN/dyi result is corrected upwards by 28%, with an additional systematic uncertainty of about 2%. No such correction is applied in the case of hpTi, since the inelastic value is close to the DS’ one, with a difference of about 1%. √ The average pT increases with particle mass and event multiplicity at all s, as predicted by all considered event generators. We note that both hpTi and ratios of hadron yields show very similar dependences on the particle multiplicity√ in the event, independently of the center-of- mass energy of the pp collisions. The s evolution of the average hadron pT provides useful information on the so-called “saturation scale” (Qsat) of the gluons in the proton [34]. Minijet- based models such as PYTHIA have an energy-dependent infrared pT cutoff of the perturbative multiparton cross sections that mimics the power-law evolution of Qsat characteristic of gluon saturation models [35]. In addition, the latter saturation models consistently connect Qsat to the impact parameter of the hadronic collision, thereby providing a natural dependence of hpTi on the ﬁnal particle multiplicity in the event.

7 Summary

Transverse momentum spectra have√ been measured for different charged hadron species produced in inelastic pp collisions at s = 13 TeV. Charged pions, kaons, and protons are iden- tiﬁed from the energy deposited in the silicon tracker and the reconstructed particle trajectory. The yields of such hadrons at rapidities |y| < 1 are studied as a function of the event charged 16 7 Summary particle multiplicity measured in the pseudorapidity range |η| < 2.4. The transverse momentum (pT) spectra are well described by ﬁts using the Tsallis-Pareto parametrization. The ratios of the yields of oppositely charged particles are close to unity, as expected in the central rapidity region for collisions at this center-of-mass energy. The average pT is found to increase with particle mass and√ event multiplicity, and shows features a slow (logarithmiclike or power-law) dependence on s.

As observed in lower-energy data, the hpTi and the ratios of particle yields are strongly correlated with event particle multiplicity. The PYTHIA8 CUETP8M1 event generator reproduces most features of the measured distributions, which represents a success of the preceding tuning of this model, and EPOSLHC also gives a satisfactory description of several aspects of the data. Although soft QCD effects are intertwined with other effects, the present results could be used to further constrain models of hadron production and to contribute to a better understanding of multiparton interactions, parton hadronization, and ﬁnal-state effects in high-energy hadron collisions.

Acknowledgments We congratulate our colleagues in the CERN accelerator departments for the excellent perfor- mance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we grate- fully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Fi- nally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMWFW and FWF (Aus- tria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Fin- land, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Ger- many); GSRT (Greece); OTKA and NIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR and RAEP (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and FEDER (Spain); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract No. 675440 (European Union); the Leventis Foun- dation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Fed- eral Science Policy Ofﬁce; the Fonds pour la Formation a` la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Council of Science and Industrial Research, India; the HOMING PLUS program of the Foun- dation for Polish Science, coﬁnanced from European Union, Regional Development Fund, the Mobility Plus program of the Ministry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Programa Clar´ın- 17

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A The CMS Collaboration Yerevan Physics Institute, Yerevan, Armenia A.M. Sirunyan, A. Tumasyan Institut f ürHochenergiephysik, Wien, Austria W. Adam, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M. Dragicevic, J. Ero,¨ M. Flechl, M. Friedl, R. Fruhwirth¨ 1, V.M. Ghete, C. Hartl, N. Hormann,¨ J. Hrubec, M. Jeitler1, A. Konig,¨ I. Kratschmer,¨ D. Liko, T. Matsushita, I. Mikulec, D. Rabady, N. Rad, B. Rahbaran, H. Rohringer, J. Schieck1, J. Strauss, W. Waltenberger, C.-E. Wulz1 Institute for Nuclear Problems, Minsk, Belarus O. Dvornikov, V. Makarenko, V. Mossolov, J. Suarez Gonzalez, V. Zykunov National Centre for Particle and High Energy Physics, Minsk, Belarus N. Shumeiko Universiteit Antwerpen, Antwerpen, Belgium S. Alderweireldt, E.A. De Wolf, X. Janssen, J. Lauwers, M. Van De Klundert, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel, A. Van Spilbeeck Vrije Universiteit Brussel, Brussel, Belgium S. Abu Zeid, F. Blekman, J. D’Hondt, N. Daci, I. De Bruyn, K. Deroover, S. Lowette, S. Moortgat, L. Moreels, A. Olbrechts, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders, I. Van Parijs UniversitéLibre de Bruxelles, Bruxelles, Belgium H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, G. Karapostoli, T. Lenzi, A. Leonard,´ J. Luetic, T. Maerschalk, A. Marinov, A. Randle-conde, T. Seva, C. Vander Velde, P. Vanlaer, D. Vannerom, R. Yonamine, F. Zenoni, F. Zhang2 Ghent University, Ghent, Belgium A. Cimmino, T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov, D. Poyraz, S. Salva, R. Schofbeck,¨ M. Tytgat, W. Van Driessche, E. Yazgan, N. Zaganidis UniversitéCatholique de Louvain, Louvain-la-Neuve, Belgium H. Bakhshiansohi, C. Beluffi3, O. Bondu, S. Brochet, G. Bruno, A. Caudron, S. De Visscher, C. Delaere, M. Delcourt, B. Francois, A. Giammanco, A. Jafari, M. Komm, G. Krintiras, V. Lemaitre, A. Magitteri, A. Mertens, M. Musich, K. Piotrzkowski, L. Quertenmont, M. Selvaggi, M. Vidal Marono, S. Wertz Universitéde Mons, Mons, Belgium N. Beliy Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil W.L. Alda´ Junior,´ F.L. Alves, G.A. Alves, L. Brito, C. Hensel, A. Moraes, M.E. Pol, P. Rebello Teles Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato4, A. Custodio,´ E.M. Da Costa, G.G. Da Silveira5, D. De Jesus Damiao, C. De Oliveira Martins, S. Fonseca De Souza, L.M. Huertas Guativa, H. Malbouisson, D. Matos Figueiredo, C. Mora Herrera, L. Mundim, H. Nogima, W.L. Prado Da Silva, A. Santoro, A. Sznajder, E.J. Tonelli Manganote4, F. Torres Da Silva De Araujo, A. Vilela Pereira 22 A The CMS Collaboration

Universidade Estadual Paulista a, Universidade Federal do ABC b, SãoPaulo, Brazil S. Ahujaa, C.A. Bernardesa, S. Dograa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb, P.G. Mercadanteb, C.S. Moona, S.F. Novaesa, Sandra S. Padulaa, D. Romero Abadb, J.C. Ruiz Vargasa Institute for Nuclear Research and Nuclear Energy, Sofia, Bulgaria A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Rodozov, S. Stoykova, G. Sultanov, M. Vutova University of Sofia, Sofia, Bulgaria A. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China W. Fang6 Institute of High Energy Physics, Beijing, China M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen7, T. Cheng, C.H. Jiang, D. Leggat, Z. Liu, F. Romeo, M. Ruan, S.M. Shaheen, A. Spiezia, J. Tao, C. Wang, Z. Wang, H. Zhang, J. Zhao State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China Y. Ban, G. Chen, Q. Li, S. Liu, Y. Mao, S.J. Qian, D. Wang, Z. Xu Universidad de Los Andes, Bogota, Colombia C. Avila, A. Cabrera, L.F. Chaparro Sierra, C. Florez, J.P. Gomez, C.F. Gonzalez´ Hernandez,´ J.D. Ruiz Alvarez8, J.C. Sanabria University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia N. Godinovic, D. Lelas, I. Puljak, P.M. Ribeiro Cipriano, T. Sculac University of Split, Faculty of Science, Split, Croatia Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, T. Susa University of Cyprus, Nicosia, Cyprus M.W. Ather, A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H. Rykaczewski Charles University, Prague, Czech Republic M. Finger9, M. Finger Jr.9 Universidad San Francisco de Quito, Quito, Ecuador E. Carrera Jarrin Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt A.A. Abdelalim10,11, Y. Mohammed12, E. Salama13,14 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia M. Kadastik, L. Perrini, M. Raidal, A. Tiko, C. Veelken Department of Physics, University of Helsinki, Helsinki, Finland P. Eerola, J. Pekkanen, M. Voutilainen 23

Helsinki Institute of Physics, Helsinki, Finland J. Hark¨ onen,¨ T. Jarvinen,¨ V. Karimaki,¨ R. Kinnunen, T. Lampen,´ K. Lassila-Perini, S. Lehti, T. Linden,´ P. Luukka, J. Tuominiemi, E. Tuovinen, L. Wendland Lappeenranta University of Technology, Lappeenranta, Finland J. Talvitie, T. Tuuva IRFU, CEA, UniversitéParis-Saclay, Gif-sur-Yvette, France M. Besancon, F. Couderc, M. Dejardin, D. Denegri, B. Fabbro, J.L. Faure, C. Favaro, F. Ferri, S. Ganjour, S. Ghosh, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, I. Kucher, E. Locci, M. Machet, J. Malcles, J. Rander, A. Rosowsky, M. Titov Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, UniversitéParis-Saclay, Palaiseau, France A. Abdulsalam, I. Antropov, S. Baffioni, F. Beaudette, P. Busson, L. Cadamuro, E. Chapon, C. Charlot, O. Davignon, R. Granier de Cassagnac, M. Jo, S. Lisniak, P. Mine,´ M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, S. Regnard, R. Salerno, Y. Sirois, A.G. Stahl Leiton, T. Strebler, Y. Yilmaz, A. Zabi, A. Zghiche Universitéde Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France J.-L. Agram15, J. Andrea, A. Aubin, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N. Chanon, C. Collard, E. Conte15, X. Coubez, J.-C. Fontaine15, D. Gele,´ U. Goerlach, A.-C. Le Bihan, P. Van Hove Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France S. Gadrat Universitéde Lyon, UniversitéClaude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucléairede Lyon, Villeurbanne, France S. Beauceron, C. Bernet, G. Boudoul, C.A. Carrillo Montoya, R. Chierici, D. Contardo, B. Courbon, P. Depasse, H. El Mamouni, J. Fay, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille, F. Lagarde, I.B. Laktineh, M. Lethuillier, L. Mirabito, A.L. Pequegnot, S. Perries, A. Popov16, V. Sordini, M. Vander Donckt, P. Verdier, S. Viret Georgian Technical University, Tbilisi, Georgia T. Toriashvili17 Tbilisi State University, Tbilisi, Georgia Z. Tsamalaidze9 RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany C. Autermann, S. Beranek, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, C. Schomakers, J. Schulz, T. Verlage RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany A. Albert, M. Brodski, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, A. Guth,¨ M. Hamer, T. Hebbeker, C. Heidemann, K. Hoepfner, S. Knutzen, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, M. Olschewski, K. Padeken, T. Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, L. Sonnenschein, D. Teyssier, S. Thuer¨ RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany V. Cherepanov, G. Flugge,¨ B. Kargoll, T. Kress, A. Kunsken,¨ J. Lingemann, T. Muller,¨ A. Nehrkorn, A. Nowack, C. Pistone, O. Pooth, A. Stahl18 24 A The CMS Collaboration

Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, U. Behrens, A.A. Bin Anuar, K. Borras19, A. Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G. Dolinska, G. Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo20, J. Garay Garcia, A. Geiser, A. Gizhko, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, A. Harb, J. Hauk, M. Hempel21, H. Jung, A. Kalogeropoulos, O. Karacheban21, M. Kasemann, J. Keaveney, C. Kleinwort, I. Korol, D. Krucker,¨ W. Lange, A. Lelek, T. Lenz, J. Leonard, K. Lipka, A. Lobanov, W. Lohmann21, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, G. Mittag, J. Mnich, A. Mussgiller, D. Pitzl, R. Placakyte, A. Raspereza, B. Roland, M.O.¨ Sahin, P. Saxena, T. Schoerner-Sadenius, S. Spannagel, N. Stefaniuk, G.P. Van Onsem, R. Walsh, C. Wissing University of Hamburg, Hamburg, Germany V. Blobel, M. Centis Vignali, A.R. Draeger, T. Dreyer, E. Garutti, D. Gonzalez, J. Haller, M. Hoffmann, A. Junkes, R. Klanner, R. Kogler, N. Kovalchuk, T. Lapsien, I. Marchesini, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, F. Pantaleo18, T. Peiffer, A. Perieanu, C. Scharf, P. Schleper, A. Schmidt, S. Schumann, J. Schwandt, H. Stadie, G. Steinbruck,¨ F.M. Stober, M. Stover,¨ H. Tholen, D. Troendle, E. Usai, L. Vanelderen, A. Vanhoefer, B. Vormwald Institut f ürExperimentelle Kernphysik, Karlsruhe, Germany M. Akbiyik, C. Barth, S. Baur, C. Baus, J. Berger, E. Butz, R. Caspart, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, S. Fink, B. Freund, R. Friese, M. Giffels, A. Gilbert, P. Goldenzweig, D. Haitz, F. Hartmann18, S.M. Heindl, U. Husemann, F. Kassel18, I. Katkov16, S. Kudella, H. Mildner, M.U. Mozer, Th. Muller,¨ M. Plagge, G. Quast, K. Rabbertz, S. Rocker,¨ F. Roscher, M. Schroder,¨ I. Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, S. Wayand, M. Weber, T. Weiler, S. Williamson, C. Wohrmann,¨ R. Wolf Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece G. Anagnostou, G. Daskalakis, T. Geralis, V.A. Giakoumopoulou, A. Kyriakis, D. Loukas, I. Topsis-Giotis National and Kapodistrian University of Athens, Athens, Greece S. Kesisoglou, A. Panagiotou, N. Saoulidou, E. Tziaferi University of Ioánnina,Ioánnina,Greece I. Evangelou, G. Flouris, C. Foudas, P. Kokkas, N. Loukas, N. Manthos, I. Papadopoulos, E. Paradas MTA-ELTE Lend ületCMS Particle and Nuclear Physics Group, EötvösLorándUniversity, Budapest, Hungary N. Filipovic, G. Pasztor Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, D. Horvath22, F. Sikler, V. Veszpremi, G. Vesztergombi23, A.J. Zsigmond Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi24, A. Makovec, J. Molnar, Z. Szillasi Institute of Physics, University of Debrecen, Debrecen, Hungary M. Bartok´ 23, P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science (IISc), Bangalore, India J.R. Komaragiri 25

National Institute of Science Education and Research, Bhubaneswar, India S. Bahinipati25, S. Bhowmik26, S. Choudhury27, P. Mal, K. Mandal, A. Nayak28, D.K. Sahoo25, N. Sahoo, S.K. Swain Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, U. Bhawandeep, R. Chawla, A.K. Kalsi, A. Kaur, M. Kaur, R. Kumar, P. Kumari, A. Mehta, M. Mittal, J.B. Singh, G. Walia University of Delhi, Delhi, India Ashok Kumar, A. Bhardwaj, B.C. Choudhary, R.B. Garg, S. Keshri, S. Malhotra, M. Naimuddin, K. Ranjan, R. Sharma, V. Sharma Saha Institute of Nuclear Physics, HBNI, Kolkata, India R. Bhattacharya, S. Bhattacharya, K. Chatterjee, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur Indian Institute of Technology Madras, Madras, India P.K. Behera Bhabha Atomic Research Centre, Mumbai, India R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty18, P.K. Netrakanti, L.M. Pant, P. Shukla, A. Topkar Tata Institute of Fundamental Research-A, Mumbai, India T. Aziz, S. Dugad, G. Kole, B. Mahakud, S. Mitra, G.B. Mohanty, B. Parida, N. Sur, B. Sutar Tata Institute of Fundamental Research-B, Mumbai, India S. Banerjee, R.K. Dewanjee, S. Ganguly, M. Guchait, Sa. Jain, S. Kumar, M. Maity26, G. Majumder, K. Mazumdar, T. Sarkar26, N. Wickramage29 Indian Institute of Science Education and Research (IISER), Pune, India S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran S. Chenarani30, E. Eskandari Tadavani, S.M. Etesami30, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi31, F. Rezaei Hosseinabadi, B. Safarzadeh32, M. Zeinali University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald INFN Sezione di Bari a, Universitàdi Bari b, Politecnico di Bari c, Bari, Italy M. Abbresciaa,b, C. Calabriaa,b, C. Caputoa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b, N. De Filippisa,c, M. De Palmaa,b, L. Fiorea, G. Iasellia,c, G. Maggia,c, M. Maggia, G. Minielloa,b, S. Mya,b, S. Nuzzoa,b, A. Pompilia,b, G. Pugliesea,c, R. Radognaa,b, A. Ranieria, G. Selvaggia,b, A. Sharmaa, L. Silvestrisa,18, R. Vendittia,b, P. Verwilligena INFN Sezione di Bologna a, Universitàdi Bologna b, Bologna, Italy G. Abbiendia, C. Battilana, D. Bonacorsia,b, S. Braibant-Giacomellia,b, L. Brigliadoria,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa, S.S. Chhibraa,b, G. Codispotia,b, M. Cuffiania,b, G.M. Dallavallea, F. Fabbria, A. Fanfania,b, D. Fasanellaa,b, P. Giacomellia, C. Grandia, L. Guiduccia,b, S. Marcellinia, G. Masettia, A. Montanaria, F.L. Navarriaa,b, A. Perrottaa, A.M. Rossia,b, T. Rovellia,b, G.P. Sirolia,b, N. Tosia,b,18 26 A The CMS Collaboration

INFN Sezione di Catania a, Universitàdi Catania b, Catania, Italy S. Albergoa,b, S. Costaa,b, A. Di Mattiaa, F. Giordanoa,b, R. Potenzaa,b, A. Tricomia,b, C. Tuvea,b INFN Sezione di Firenze a, Universitàdi Firenze b, Firenze, Italy G. Barbaglia, V. Ciullia,b, C. Civininia, R. D’Alessandroa,b, E. Focardia,b, P. Lenzia,b, M. Meschinia, S. Paolettia, L. Russoa,33, G. Sguazzonia, D. Stroma, L. Viliania,b,18 INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera18 INFN Sezione di Genova a, Universitàdi Genova b, Genova, Italy V. Calvellia,b, F. Ferroa, M.R. Mongea,b, E. Robuttia, S. Tosia,b INFN Sezione di Milano-Bicocca a, Universitàdi Milano-Bicocca b, Milano, Italy L. Brianzaa,b,18, F. Brivioa,b, V. Ciriolo, M.E. Dinardoa,b, S. Fiorendia,b,18, S. Gennaia, A. Ghezzia,b, P. Govonia,b, M. Malbertia,b, S. Malvezzia, R.A. Manzonia,b, D. Menascea, L. Moronia, M. Paganonia,b, D. Pedrinia, S. Pigazzinia,b, S. Ragazzia,b, T. Tabarelli de Fatisa,b INFN Sezione di Napoli a, Universitàdi Napoli ’Federico II’ b, Napoli, Italy, Universitàdella Basilicata c, Potenza, Italy, UniversitàG. Marconi d, Roma, Italy S. Buontempoa, N. Cavalloa,c, G. De Nardo, S. Di Guidaa,d,18, F. Fabozzia,c, F. Fiengaa,b, A.O.M. Iorioa,b, L. Listaa, S. Meolaa,d,18, P. Paoluccia,18, C. Sciaccaa,b, F. Thyssena INFN Sezione di Padova a, Universitàdi Padova b, Padova, Italy, Universitàdi Trento c, Trento, Italy P. Azzia,18, N. Bacchettaa, L. Benatoa,b, D. Biselloa,b, A. Bolettia,b, R. Carlina,b, A. Carvalho Antunes De Oliveiraa,b, P. Checchiaa, M. Dall’Ossoa,b, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F. Gasparinia,b, U. Gasparinia,b, A. Gozzelinoa, S. Lacapraraa, M. Margonia,b, A.T. Meneguzzoa,b, J. Pazzinia,b, N. Pozzobona,b, P. Ronchesea,b, F. Simonettoa,b, E. Torassaa, M. Zanettia,b, P. Zottoa,b, G. Zumerlea,b INFN Sezione di Pavia a, Universitàdi Pavia b, Pavia, Italy A. Braghieria, F. Fallavollitaa,b, A. Magnania,b, P. Montagnaa,b, S.P. Rattia,b, V. Rea, C. Riccardia,b, P. Salvinia, I. Vaia,b, P. Vituloa,b INFN Sezione di Perugia a, Universitàdi Perugia b, Perugia, Italy L. Alunni Solestizia,b, G.M. Bileia, D. Ciangottinia,b, L. Fano` a,b, P. Laricciaa,b, R. Leonardia,b, G. Mantovania,b, V. Mariania,b, M. Menichellia, A. Sahaa, A. Santocchiaa,b INFN Sezione di Pisa a, Universitàdi Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy K. Androsova,33, P. Azzurria,18, G. Bagliesia, J. Bernardinia, T. Boccalia, R. Castaldia, M.A. Cioccia,33, R. Dell’Orsoa, S. Donatoa,c, G. Fedi, A. Giassia, M.T. Grippoa,33, F. Ligabuea,c, T. Lomtadzea, L. Martinia,b, A. Messineoa,b, F. Pallaa, A. Rizzia,b, A. Savoy-Navarroa,34, P. Spagnoloa, R. Tenchinia, G. Tonellia,b, A. Venturia, P.G. Verdinia INFN Sezione di Roma a, Sapienza Universitàdi Roma b, Rome, Italy L. Baronea,b, F. Cavallaria, M. Cipriania,b, D. Del Rea,b,18, M. Diemoza, S. Gellia,b, E. Longoa,b, F. Margarolia,b, B. Marzocchia,b, P. Meridiania, G. Organtinia,b, R. Paramattia,b, F. Preiatoa,b, S. Rahatloua,b, C. Rovellia, F. Santanastasioa,b INFN Sezione di Torino a, Universitàdi Torino b, Torino, Italy, Universitàdel Piemonte Orientale c, Novara, Italy N. Amapanea,b, R. Arcidiaconoa,c,18, S. Argiroa,b, M. Arneodoa,c, N. Bartosika, R. Bellana,b, C. Biinoa, N. Cartigliaa, F. Cennaa,b, M. Costaa,b, R. Covarellia,b, A. Deganoa,b, N. Demariaa, L. Fincoa,b, B. Kiania,b, C. Mariottia, S. Masellia, E. Migliorea,b, V. Monacoa,b, E. Monteila,b, 27

M. Montenoa, M.M. Obertinoa,b, L. Pachera,b, N. Pastronea, M. Pelliccionia, G.L. Pinna Angionia,b, F. Raveraa,b, A. Romeroa,b, M. Ruspaa,c, R. Sacchia,b, K. Shchelinaa,b, V. Solaa, A. Solanoa,b, A. Staianoa, P. Traczyka,b INFN Sezione di Trieste a, Universit`adi Trieste b, Trieste, Italy S. Belfortea, M. Casarsaa, F. Cossuttia, G. Della Riccaa,b, A. Zanettia Kyungpook National University, Daegu, Korea D.H. Kim, G.N. Kim, M.S. Kim, S. Lee, S.W. Lee, Y.D. Oh, S. Sekmen, D.C. Son, Y.C. Yang Chonbuk National University, Jeonju, Korea A. Lee Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea H. Kim Hanyang University, Seoul, Korea J.A. Brochero Cifuentes, T.J. Kim Korea University, Seoul, Korea S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, K. Lee, K.S. Lee, S. Lee, J. Lim, S.K. Park, Y. Roh Seoul National University, Seoul, Korea J. Almond, J. Kim, H. Lee, S.B. Oh, B.C. Radburn-Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul, Korea M. Choi, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park, G. Ryu, M.S. Ryu Sungkyunkwan University, Suwon, Korea Y. Choi, J. Goh, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia I. Ahmed, Z.A. Ibrahim, M.A.B. Md Ali35, F. Mohamad Idris36, W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz37, A. Hernandez-Almada, R. Lopez-Fernandez, R. Magana˜ Villalba, J. Mejia Guisao, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico S. Carpinteyro, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Aut´onomade San Luis Potos´ı, San Luis Potos´ı, Mexico A. Morelos Pineda University of Auckland, Auckland, New Zealand D. Krofcheck University of Canterbury, Christchurch, New Zealand P.H. Butler 28 A The CMS Collaboration

National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, W.A. Khan, A. Saddique, M.A. Shah, M. Shoaib, M. Waqas National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Gorski,´ M. Kazana, K. Nawrocki, K. Romanowska-Rybinska, M. Szleper, P. Zalewski Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland K. Bunkowski, A. Byszuk38, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, M. Walczak Laborat´oriode Instrumenta¸c˜aoe F´ısicaExperimental de Part´ıculas,Lisboa, Portugal P. Bargassa, C. Beirao˜ Da Cruz E Silva, B. Calpas, A. Di Francesco, P. Faccioli, P.G. Ferreira Parracho, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M.V. Nemallapudi, J. Rodrigues Antunes, J. Seixas, O. Toldaiev, D. Vadruccio, J. Varela Joint Institute for Nuclear Research, Dubna, Russia S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev, V. Karjavin, A. Lanev, A. Malakhov, V. Matveev39,40, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia L. Chtchipounov, V. Golovtsov, Y. Ivanov, V. Kim41, E. Kuznetsova42, V. Murzin, V. Oreshkin, V. Sulimov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, M. Toms, E. Vlasov, A. Zhokin Moscow Institute of Physics and Technology, Moscow, Russia T. Aushev, A. Bylinkin40 National Research Nuclear University ’Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia R. Chistov43, M. Danilov43, E. Popova P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin40, I. Dremin40, M. Kirakosyan, A. Leonidov40, A. Terkulov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia A. Baskakov, A. Belyaev, E. Boos, A. Gribushin, L. Khein, V. Klyukhin, O. Kodolova, I. Lokhtin, O. Lukina, I. Miagkov, S. Obraztsov, S. Petrushanko, V. Savrin, A. Snigirev, P. Volkov Novosibirsk State University (NSU), Novosibirsk, Russia V. Blinov44, Y.Skovpen44, D. Shtol44 State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin, D. Konstantinov, V. Krychkine, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov 29

University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia P. Adzic45, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain J. Alcaraz Maestre, M. Barrio Luna, E. Calvo, M. Cerrada, M. Chamizo Llatas, N. Colino, B. De La Cruz, A. Delgado Peris, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fernandez´ Ramos, J. Flix, M.C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, E. Navarro De Martino, A. Perez-Calero´ Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares Universidad Autónomade Madrid, Madrid, Spain J.F. de Troconiz,´ M. Missiroli, D. Moran Universidad de Oviedo, Oviedo, Spain J. Cuevas, J. Fernandez Menendez, I. Gonzalez Caballero, J.R. Gonzalez´ Fernandez,´ E. Palencia Cortezon, S. Sanchez Cruz, I. Suarez´ Andres,´ P. Vischia, J.M. Vizan Garcia Instituto de F´ısicade Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain I.J. Cabrillo, A. Calderon, E. Curras, M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, F. Matorras, J. Piedra Gomez, T. Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte CERN, European Organization for Nuclear Research, Geneva, Switzerland D. Abbaneo, E. Auffray, G. Auzinger, P. Baillon, A.H. Ball, D. Barney, P. Bloch, A. Bocci, C. Botta, T. Camporesi, R. Castello, M. Cepeda, G. Cerminara, Y. Chen, D. d’Enterria, A. Dabrowski, V. Daponte, A. David, M. De Gruttola, A. De Roeck, E. Di Marco46, M. Dobson, B. Dorney, T. du Pree, D. Duggan, M. Dunser,¨ N. Dupont, A. Elliott-Peisert, P. Everaerts, S. Fartoukh, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, K. Gill, M. Girone, F. Glege, D. Gulhan, S. Gundacker, M. Guthoff, P. Harris, J. Hegeman, V. Innocente, P. Janot, J. Kieseler, H. Kirschenmann, V. Knunz,¨ A. Kornmayer18, M.J. Kortelainen, K. Kousouris, M. Krammer1, C. Lange, P. Lecoq, C. Lourenço, M.T. Lucchini, L. Malgeri, M. Mannelli, A. Martelli, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, P. Milenovic47, F. Moortgat, S. Morovic, M. Mulders, H. Neugebauer, S. Orfanelli, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfeiffer, M. Pierini, A. Racz, T. Reis, G. Rolandi48, M. Rovere, H. Sakulin, J.B. Sauvan, C. Schafer,¨ C. Schwick, M. Seidel, A. Sharma, P. Silva, P. Sphicas49, J. Steggemann, M. Stoye, Y. Takahashi, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns50, G.I. Veres23, M. Verweij, N. Wardle, H.K. Wohri,¨ A. Zagozdzinska38, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland W. Bertl, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe, S.A. Wiederkehr Institute for Particle Physics, ETH Zurich, Zurich, Switzerland F. Bachmair, L. Bani,¨ L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donega,` C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, W. Lustermann, B. Mangano, M. Marionneau, P. Martinez Ruiz del Arbol, M. Masciovecchio, M.T. Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandolfi, J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Rossini, M. Schonenberger,¨ A. Starodumov51, V.R. Tavolaro, K. Theofilatos, R. Wallny UniversitätZ ürich,Zurich, Switzerland T.K. Aarrestad, C. Amsler52, L. Caminada, M.F. Canelli, A. De Cosa, C. Galloni, A. Hinzmann, 30 A The CMS Collaboration

T. Hreus, B. Kilminster, J. Ngadiuba, D. Pinna, G. Rauco, P. Robmann, D. Salerno, C. Seitz, Y. Yang, A. Zucchetta National Central University, Chung-Li, Taiwan V. Candelise, T.H. Doan, Sh. Jain, R. Khurana, M. Konyushikhin, C.M. Kuo, W. Lin, A. Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, P. Chang, Y.H. Chang, Y. Chao, K.F. Chen, P.H. Chen, F. Fiori, W.-S. Hou, Y. Hsiung, Y.F. Liu, R.-S. Lu, M. Minano˜ Moya, E. Paganis, A. Psallidas, J.f. Tsai Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, Thailand B. Asavapibhop, G. Singh, N. Srimanobhas, N. Suwonjandee Cukurova University, Physics Department, Science and Art Faculty, Adana, Turkey A. Adiguzel, M.N. Bakirci53, S. Cerci54, S. Damarseckin, Z.S. Demiroglu, C. Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, I. Hos55, E.E. Kangal56, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G. Onengut57, K. Ozdemir58, B. Tali54, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey B. Bilin, S. Bilmis, B. Isildak59, G. Karapinar60, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gulmez,¨ M. Kaya61, O. Kaya62, E.A. Yetkin63, T. Yetkin64 Istanbul Technical University, Istanbul, Turkey A. Cakir, K. Cankocak, S. Sen65 Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine B. Grynyov National Scientiﬁc Center, Kharkov Institute of Physics and Technology, Kharkov, Ukraine L. Levchuk, P. Sorokin University of Bristol, Bristol, United Kingdom R. Aggleton, F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, H. Flacher, J. Goldstein, M. Grimes, G.P. Heath, H.F. Heath, J. Jacob, L. Kreczko, C. Lucas, D.M. Newbold66, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, D. Smith, V.J. Smith Rutherford Appleton Laboratory, Didcot, United Kingdom K.W. Bell, A. Belyaev67, C. Brew, R.M. Brown, L. Calligaris, D. Cieri, D.J.A. Cockerill, J.A. Coughlan, K. Harder, S. Harper, E. Olaiya, D. Petyt, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams Imperial College, London, United Kingdom M. Baber, R. Bainbridge, O. Buchmuller, A. Bundock, D. Burton, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, R. Di Maria, P. Dunne, A. Elwood, D. Futyan, Y. Haddad, G. Hall, G. Iles, T. James, R. Lane, C. Laner, R. Lucas66, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, J. Nash, A. Nikitenko51, J. Pela, B. Penning, M. Pesaresi, D.M. Raymond, A. Richards, A. Rose, E. Scott, C. Seez, S. Summers, A. Tapper, K. Uchida, M. Vazquez Acosta68, T. Virdee18, J. Wright, S.C. Zenz Brunel University, Uxbridge, United Kingdom J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, I.D. Reid, P. Symonds, L. Teodorescu, M. Turner 31

Baylor University, Waco, USA A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika Catholic University of America, Washington, USA R. Bartek, A. Dominguez The University of Alabama, Tuscaloosa, USA A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University, Boston, USA D. Arcaro, A. Avetisyan, T. Bose, D. Gastler, D. Rankin, C. Richardson, J. Rohlf, L. Sulak, D. Zou Brown University, Providence, USA G. Benelli, D. Cutts, A. Garabedian, J. Hakala, U. Heintz, J.M. Hogan, O. Jesus, K.H.M. Kwok, E. Laird, G. Landsberg, Z. Mao, M. Narain, S. Piperov, S. Sagir, E. Spencer, R. Syarif University of California, Davis, Davis, USA R. Breedon, D. Burns, M. Calderon De La Barca Sanchez, S. Chauhan, M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, M. Gardner, W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout, M. Shi, J. Smith, M. Squires, D. Stolp, K. Tos, M. Tripathi University of California, Los Angeles, USA M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M. Ignatenko, N. Mccoll, D. Saltzberg, C. Schnaible, V. Valuev, M. Weber University of California, Riverside, Riverside, USA E. Bouvier, K. Burt, R. Clare, J. Ellison, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, J. Heilman, P. Jandir, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I. Paneva, A. Shrinivas, W. Si, H. Wei, S. Wimpenny, B. R. Yates University of California, San Diego, La Jolla, USA J.G. Branson, G.B. Cerati, S. Cittolin, M. Derdzinski, R. Gerosa, A. Holzner, D. Klein, V. Krutelyov, J. Letts, I. Macneill, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A. Vartak, S. Wasserbaech69, C. Welke, J. Wood, F. Wurthwein,¨ A. Yagil, G. Zevi Della Porta University of California, Santa Barbara - Department of Physics, Santa Barbara, USA N. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta, M. Franco Sevilla, C. George, F. Golf, L. Gouskos, J. Gran, R. Heller, J. Incandela, S.D. Mullin, A. Ovcharova, H. Qu, J. Richman, D. Stuart, I. Suarez, J. Yoo California Institute of Technology, Pasadena, USA D. Anderson, J. Bendavid, A. Bornheim, J. Bunn, J. Duarte, J.M. Lawhorn, A. Mott, H.B. Newman, C. Pena, M. Spiropulu, J.R. Vlimant, S. Xie, R.Y. Zhu Carnegie Mellon University, Pittsburgh, USA M.B. Andrews, T. Ferguson, M. Paulini, J. Russ, M. Sun, H. Vogel, I. Vorobiev, M. Weinberg University of Colorado Boulder, Boulder, USA J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, S. Leontsinis, T. Mulholland, K. Stenson, S.R. Wagner Cornell University, Ithaca, USA J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, G. Nicolas Kaufman, 32 A The CMS Collaboration

J.R. Patterson, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, S.M. Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fairfield University, Fairfield, USA D. Winn Fermi National Accelerator Laboratory, Batavia, USA S. Abdullin, M. Albrow, G. Apollinari, A. Apresyan, S. Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G. Bolla, K. Burkett, J.N. Butler, H.W.K. Cheung, F. Chlebana, S. Cihangir†, M. Cremonesi, V.D. Elvira, I. Fisk, J. Freeman, E. Gottschalk, L. Gray, D. Green, S. Grunendahl,¨ O. Gutsche, D. Hare, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B. Klima, B. Kreis, S. Lammel, J. Linacre, D. Lincoln, R. Lipton, M. Liu, T. Liu, R. Lopes De Sa,´ J. Lykken, K. Maeshima, N. Magini, J.M. Marraffino, S. Maruyama, D. Mason, P. McBride, P. Merkel, S. Mrenna, S. Nahn, V. O’Dell, K. Pedro, O. Prokofyev, G. Rakness, L. Ristori, E. Sexton-Kennedy, A. Soha, W.J. Spalding, L. Spiegel, S. Stoynev, J. Strait, N. Strobbe, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, C. Vernieri, M. Verzocchi, R. Vidal, M. Wang, H.A. Weber, A. Whitbeck, Y. Wu University of Florida, Gainesville, USA D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerhoff, A. Carnes, M. Carver, D. Curry, S. Das, R.D. Field, I.K. Furic, J. Konigsberg, A. Korytov, J.F. Low, P. Ma, K. Matchev, H. Mei, G. Mitselmakher, D. Rank, L. Shchutska, D. Sperka, L. Thomas, J. Wang, S. Wang, J. Yelton Florida International University, Miami, USA S. Linn, P. Markowitz, G. Martinez, J.L. Rodriguez Florida State University, Tallahassee, USA A. Ackert, T. Adams, A. Askew, S. Bein, S. Hagopian, V. Hagopian, K.F. Johnson, T. Kolberg, H. Prosper, A. Santra, R. Yohay Florida Institute of Technology, Melbourne, USA M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T. Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, USA M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, I. Bucinskaite, R. Cavanaugh, O. Evdokimov, L. Gauthier, C.E. Gerber, D.J. Hofman, K. Jung, I.D. Sandoval Gonzalez, N. Varelas, H. Wang, Z. Wu, M. Zakaria, J. Zhang The University of Iowa, Iowa City, USA B. Bilki70, W. Clarida, K. Dilsiz, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya71, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul, Y. Onel, F. Ozok72, A. Penzo, C. Snyder, E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, USA B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan, P. Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao, C. You The University of Kansas, Lawrence, USA A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, J. Castle, L. Forthomme, R.P. Kenny III, S. Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, S. Sanders, R. Stringer, J.D. Tapia Takaki, Q. Wang Kansas State University, Manhattan, USA A. Ivanov, K. Kaadze, Y. Maravin, A. Mohammadi, L.K. Saini, N. Skhirtladze, S. Toda 33

Lawrence Livermore National Laboratory, Livermore, USA F. Rebassoo, D. Wright University of Maryland, College Park, USA C. Anelli, A. Baden, O. Baron, A. Belloni, B. Calvert, S.C. Eno, C. Ferraioli, J.A. Gomez, N.J. Hadley, S. Jabeen, G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, F. Ricci-Tam, Y.H. Shin, A. Skuja, M.B. Tonjes, S.C. Tonwar Massachusetts Institute of Technology, Cambridge, USA D. Abercrombie, B. Allen, A. Apyan, V. Azzolini, R. Barbieri, A. Baty, R. Bi, K. Bierwagen, S. Brandt, W. Busza, I.A. Cali, M. D’Alfonso, Z. Demiragli, G. Gomez Ceballos, M. Goncharov, D. Hsu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi, K. Krajczar, Y.S. Lai, Y.-J. Lee, A. Levin, P.D. Luckey, B. Maier, A.C. Marini, C. Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, J. Salfeld-Nebgen, G.S.F. Stephans, K. Tatar, D. Velicanu, J. Wang, T.W. Wang, B. Wyslouch University of Minnesota, Minneapolis, USA A.C. Benvenuti, R.M. Chatterjee, A. Evans, P. Hansen, S. Kalafut, S.C. Kao, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, N. Tambe, J. Turkewitz University of Mississippi, Oxford, USA J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, R. Gonzalez Suarez, R. Kamalieddin, I. Kravchenko, A. Malta Rodrigues, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger State University of New York at Buffalo, Buffalo, USA M. Alyari, J. Dolen, A. Godshalk, C. Harrington, I. Iashvili, J. Kaisen, D. Nguyen, A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, USA G. Alverson, E. Barberis, A. Hortiangtham, A. Massironi, D.M. Morse, D. Nash, T. Orimoto, R. Teixeira De Lima, D. Trocino, R.-J. Wang, D. Wood Northwestern University, Evanston, USA S. Bhattacharya, O. Charaf, K.A. Hahn, A. Kumar, N. Mucia, N. Odell, B. Pollack, M.H. Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, USA N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N. Kellams, K. Lannon, N. Marinelli, F. Meng, C. Mueller, Y. Musienko39, M. Planer, A. Reinsvold, R. Ruchti, N. Rupprecht, G. Smith, S. Taroni, M. Wayne, M. Wolf, A. Woodard The Ohio State University, Columbus, USA J. Alimena, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A. Hart, C. Hill, R. Hughes, W. Ji, B. Liu, W. Luo, D. Puigh, B.L. Winer, H.W. Wulsin Princeton University, Princeton, USA S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, D. Lange, J. Luo, D. Marlow, T. Medvedeva, K. Mei, I. Ojalvo, J. Olsen, C. Palmer, P. Piroue,´ D. Stickland, A. Svyatkovskiy, C. Tully University of Puerto Rico, Mayaguez, USA S. Malik 34 A The CMS Collaboration

Purdue University, West Lafayette, USA A. Barker, V.E. Barnes, S. Folgueras, L. Gutay, M.K. Jha, M. Jones, A.W. Jung, A. Khatiwada, D.H. Miller, N. Neumeister, J.F. Schulte, X. Shi, J. Sun, F. Wang, W. Xie Purdue University Northwest, Hammond, USA N. Parashar, J. Stupak Rice University, Houston, USA A. Adair, B. Akgun, Z. Chen, K.M. Ecklund, F.J.M. Geurts, M. Guilbaud, W. Li, B. Michlin, M. Northup, B.P. Padley, J. Roberts, J. Rorie, Z. Tu, J. Zabel University of Rochester, Rochester, USA B. Betchart, A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, T. Ferbel, M. Galanti, A. Garcia- Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, K.H. Lo, P. Tan, M. Verzetti Rutgers, The State University of New Jersey, Piscataway, USA A. Agapitos, J.P. Chou, Y. Gershtein, T.A. Gomez´ Espinosa, E. Halkiadakis, M. Heindl, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D. Shefﬁeld, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, USA A.G. Delannoy, M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M University, College Station, USA O. Bouhali73, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, E. Juska, T. Kamon74, R. Mueller, Y. Pakhotin, R. Patel, A. Perloff, L. Pernie,` D. Rathjens, A. Safonov, A. Tatarinov, K.A. Ulmer Texas Tech University, Lubbock, USA N. Akchurin, J. Damgov, F. De Guio, C. Dragoiu, P.R. Dudero, J. Faulkner, E. Gurpinar, S. Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang Vanderbilt University, Nashville, USA S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia, Charlottesville, USA M.W. Arenton, P. Barria, B. Cox, J. Goodell, R. Hirosky, A. Ledovskoy, H. Li, C. Neu, T. Sinthuprasith, X. Sun, Y. Wang, E. Wolfe, F. Xia Wayne State University, Detroit, USA C. Clarke, R. Harr, P.E. Karchin, J. Sturdy University of Wisconsin - Madison, Madison, WI, USA D.A. Belknap, J. Buchanan, C. Caillol, S. Dasu, L. Dodd, S. Duric, B. Gomber, M. Grothe, M. Herndon, A. Herve,´ P. Klabbers, A. Lanaro, A. Levine, K. Long, R. Loveless, T. Perry, G.A. Pierro, G. Polese, T. Ruggles, A. Savin, N. Smith, W.H. Smith, D. Taylor, N. Woods †: Deceased 1: Also at Vienna University of Technology, Vienna, Austria 2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China 3: Also at Institut Pluridisciplinaire Hubert Curien (IPHC), Universite´ de Strasbourg, CNRS/IN2P3, Strasbourg, France 35

4: Also at Universidade Estadual de Campinas, Campinas, Brazil 5: Also at Universidade Federal de Pelotas, Pelotas, Brazil 6: Also at Universite´ Libre de Bruxelles, Bruxelles, Belgium 7: Also at Deutsches Elektronen-Synchrotron, Hamburg, Germany 8: Also at Universidad de Antioquia, Medellin, Colombia 9: Also at Joint Institute for Nuclear Research, Dubna, Russia 10: Also at Helwan University, Cairo, Egypt 11: Now at Zewail City of Science and Technology, Zewail, Egypt 12: Now at Fayoum University, El-Fayoum, Egypt 13: Also at British University in Egypt, Cairo, Egypt 14: Now at Ain Shams University, Cairo, Egypt 15: Also at Universite´ de Haute Alsace, Mulhouse, France 16: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia 17: Also at Tbilisi State University, Tbilisi, Georgia 18: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 19: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany 20: Also at University of Hamburg, Hamburg, Germany 21: Also at Brandenburg University of Technology, Cottbus, Germany 22: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 23: Also at MTA-ELTE Lendulet¨ CMS Particle and Nuclear Physics Group, Eotv¨ os¨ Lorand´ University, Budapest, Hungary 24: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary 25: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India 26: Also at University of Visva-Bharati, Santiniketan, India 27: Also at Indian Institute of Science Education and Research, Bhopal, India 28: Also at Institute of Physics, Bhubaneswar, India 29: Also at University of Ruhuna, Matara, Sri Lanka 30: Also at Isfahan University of Technology, Isfahan, Iran 31: Also at Yazd University, Yazd, Iran 32: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 33: Also at Universita` degli Studi di Siena, Siena, Italy 34: Also at Purdue University, West Lafayette, USA 35: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 36: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 37: Also at Consejo Nacional de Ciencia y Tecnolog´ıa, Mexico city, Mexico 38: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 39: Also at Institute for Nuclear Research, Moscow, Russia 40: Now at National Research Nuclear University ’Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia 41: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 42: Also at University of Florida, Gainesville, USA 43: Also at P.N. Lebedev Physical Institute, Moscow, Russia 44: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia 45: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 46: Also at INFN Sezione di Roma; Sapienza Universita` di Roma, Rome, Italy 47: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia 36 A The CMS Collaboration

48: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy 49: Also at National and Kapodistrian University of Athens, Athens, Greece 50: Also at Riga Technical University, Riga, Latvia 51: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 52: Also at Albert Einstein Center for Fundamental Physics, Bern, Switzerland 53: Also at Gaziosmanpasa University, Tokat, Turkey 54: Also at Adiyaman University, Adiyaman, Turkey 55: Also at Istanbul Aydin University, Istanbul, Turkey 56: Also at Mersin University, Mersin, Turkey 57: Also at Cag University, Mersin, Turkey 58: Also at Piri Reis University, Istanbul, Turkey 59: Also at Ozyegin University, Istanbul, Turkey 60: Also at Izmir Institute of Technology, Izmir, Turkey 61: Also at Marmara University, Istanbul, Turkey 62: Also at Kafkas University, Kars, Turkey 63: Also at Istanbul Bilgi University, Istanbul, Turkey 64: Also at Yildiz Technical University, Istanbul, Turkey 65: Also at Hacettepe University, Ankara, Turkey 66: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 67: Also at School of Physics and Astronomy, University of Southampton, Southampton, United Kingdom 68: Also at Instituto de Astrof´ısica de Canarias, La Laguna, Spain 69: Also at Utah Valley University, Orem, USA 70: Also at Argonne National Laboratory, Argonne, USA 71: Also at Erzincan University, Erzincan, Turkey 72: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 73: Also at Texas A&M University at Qatar, Doha, Qatar 74: Also at Kyungpook National University, Daegu, Korea